Content-based image retrieval (CBIR) is gradually gaining momentum among Internet users nowadays. Some websites or search engines offer content-based image search services to Internet users. Specifically, a user submits a query image which is similar to his/her desired image to a website or search engine that provides CBIR services. Based on the query image, the website or search engine subsequently returns one or more stored images to the user. In order to allow efficient retrieval of stored images, the website or search engine represents or encodes the stored images in terms of image features. The website or search engine compares the image features of the stored images with image features of the query image, and retrieves one or more stored images that have image features similar to the image features of the query image.
Given the increasing popularity of CBIR services, academic or business communities have conducted significant research to determine an image representation that can provide efficient comparison and retrieval of images. A number of algorithms and strategies such as Bags of Words (BOW) have been proposed. However, these proposed algorithms or strategies are either restricted to a small set of images or are too computationally intensive to be performed in real time.